UC4 - Flexible Transportation

Modern transport systems generate large volumes of heterogeneous mobility data (GPS traces, geofence events, user-declared places, mobility options, predictions). UC4 transforms noisy, fragmented signals into coherent daily mobility timelines for transport planners via the Pythia pipeline in ExtremeXP framework. Challenges include irregular GPS sampling, noise/accuracy issues, activity/mode ambiguity, lack of temporal/spatial coherence. CAW reconstructs day-level timelines from master JSON files per user integrating raw GPS, user places (home/work/other), geofence events, mobility options, predictions/configurations. Objectives: 1) Ingest/contextualize data; 2) Preprocess/segment trajectories; 3) Build segment/trip dictionary; 4) Enrich with modes/activities/geofences/place corrections; 5) Enforce temporal/spatial coherence. 

Part of the ExtremeXP project, co-funded by the European Union Horizon Program HORIZON CL4-2022-DATA-01-01 under Grant Agreement No. 101093164. Project website: https://extremexp.eu/.